ECG measuring apparatuses are primarily used for the measurement and monitoring of the cardiac function of a patient, and typically the total voltage of the electrical activity in the cardiac muscle fibers is measured as the so-called “ECG signal” via at least two electrodes.
However there are also further applications. For example ECG signals are also used in medical imaging to generate trigger signals. During imaging, information about the cardiac phase is obtained via the ECG signal in order thereby to synchronize the imaging with the cardiac activity. Particularly in the case of imaging procedures that require a longer recording time, cardiac recordings, or indeed recordings of areas that are moved by the heartbeat, can be produced to a high quality in this way.
ECG measuring apparatuses are also used for the in-situ recording of ECG signals during an examination of a patient by means of a magnetic resonance device. On account of the strong gradient fields and high-frequency fields used in the magnetic resonance device, however, particular demands are placed in this case on the ECG measuring apparatus by an operation in the magnetic resonance device, in order to prevent reciprocal interference between the magnetic resonance device and the ECG measuring apparatus. ECG measuring apparatuses, which are magnetic-resonance-compatible within the meaning described above, are available on the market.
However magnetic fields that vary over time, such as those used in the magnetic resonance device as magnetic gradient fields for position encoding, continue to pose a major problem for reliable ECG signal measurement. In accordance with the law of induction such magnetic fields that vary over time generate noise voltages that are coupled into the ECG signal recorded by the ECG electrodes as noise. Magnetically-generated noise signals of this type are superimposed on and corrupt the ECG signal generated by the heart. A signal data record U1(t) measured at a first channel of the ECG measuring apparatus then contains not only the desired ECG signal U1 EKG(t) at the time t, but also a superposition of the ECG signal with the noise voltages S1(t) generated by induction at the time t:U1(t)=U1 EKG(t)+S1(t).
This noise is highly undesirable. In order to synchronize a recording of a magnetic resonance image with the heartbeat, a reliable identification of the R-wave in the ECG signal is required. The noise signals can be interpreted erroneously as an R-wave e.g. on account of their often similar shape, and can thus cause a magnetic resonance image to be recorded spuriously. On the other hand it may also be the case that a “real” R-wave is not recognized as such on account of the superimposed noise signals. This frequently causes a considerable deterioration in image quality.
From the publications “Restoration of Electrophysiological Signals Distorted by Inductive Effects of Magnetic Field Gradients During MR Sequences”; Jacques Felblinger, Johannes Slotboom, Roland Kreis, Bruno Jung, Chris Boesch; Magnetic Resonance in Medicine 41:715-721 (1999) and “Noise Cancellation Signal Processing Method and Computer System for Improved Real-Time Electrocardiogram Artifact Correction during MRI Data Acquisition”; Freddy Odille, Cedric Pasquier, Roger Abächerli, Pierre-Andre Vuissoz, Gary P. Zientara, Jacques Felblinger; IEEE Transactions on Biomedical Engineering, VOL. 54, NO. 4, APRIL 2007, a method is known in which an estimation of the noise artifacts caused by the gradient fields and thus of the noise voltages is performed. The estimated noise voltage of an ECG channel S1(t) est is then subtracted from the ECG signals U1(t) measured on the same ECG channel in order to obtain a corrected ECG signal U1 korr(t):U1 korr(t)=U1 EKG(t)+S1(t)−S1 est(t).
It is assumed here that the noise voltages S1(t) can be separated into noise voltages S1x(t), S1y(t) and S1z(t), each of which is caused by the known currents Ix(t), Iy(t) and Iz(t) that are impressed on the x-, y- and z-axis gradient coils:
                              S          ⁢                                          ⁢          1          ⁢                      (            t            )                          =                ⁢                              S            ⁢                                                  ⁢            1            ⁢                          x              ⁡                              (                t                )                                              +                      S            ⁢                                                  ⁢            1            ⁢                          y              ⁡                              (                t                )                                              +                      S            ⁢                                                  ⁢            1            ⁢                          z              ⁡                              (                t                )                                                                            =                ⁢                              h            ⁢                                                  ⁢            Ix            ⁢                                                  ⁢            U            ⁢                                                  ⁢            1            ⁢                          (              t              )                        *                          Ix              ⁡                              (                t                )                                              +                      h            ⁢                                                  ⁢            Iy            ⁢                                                  ⁢            U            ⁢                                                  ⁢            1            ⁢                          (              t              )                        *                          Iy              ⁡                              (                t                )                                              +                                                ⁢                  h          ⁢                                          ⁢          Iz          ⁢                                          ⁢          U          ⁢                                          ⁢          1          ⁢                      (            t            )                    *                                    Iz              ⁡                              (                t                )                                      .                              where h Ii U1(t) (i=x,y,z) represents the corresponding impulse response that characterizes the influence on the ECG signal U1(t) exerted by the current Ii(t) through the i-axis gradient coil. “*” indicates a system-theoretical convolution.
Here the x-, y- and z-axes are perpendicular to each other, with the x-axis typically corresponding to a normal vector on a sagittal plane, the y-axis to a normal vector on a coronary plane, and the z-axis to a normal vector on a transverse plane, through a patient located in a magnetic resonance device.
The aforementioned impulse responses h Ii U1(t) are estimated by measuring e.g. ECG signals U1(t) in training measurements if in each case only one of the gradient coils is fed a current Ii(t) not equal to zero, such that the following applies e.g. where i=x:U1(t)=U1 EKG(t)+h Ix U1(t)*Ix(t).
The impulse response h Ix U1(t) can be estimated from this equation by means of calculations in the frequency range. The contribution made by U1 EKG(t) can then be deducted e.g. by repeated measurement and subsequent averaging of U1(t). The same procedure is performed for further impulse responses. The result is as follows:
      S    ⁢                  ⁢    1    ⁢                  ⁢          est      ⁡              (        t        )              =            h      ⁢                          ⁢      Ix      ⁢                          ⁢      U      ⁢                          ⁢      1      ⁢                          ⁢              est        ⁡                  (          t          )                    *              Ix        ⁡                  (          t          )                      +          h      ⁢                          ⁢      Iy      ⁢                          ⁢      U      ⁢                          ⁢      1      ⁢                          ⁢              est        ⁡                  (          t          )                    *              Iy        ⁡                  (          t          )                      +          h      ⁢                          ⁢      Iz      ⁢                          ⁢      U      ⁢                          ⁢      1      ⁢                          ⁢              est        ⁡                  (          t          )                    *                        Iz          ⁡                      (            t            )                          .            
For more precise details, reference is made to the aforementioned prior art.
Good results are achieved with this method when ECG signals are corrected that were measured under the same conditions which also prevailed during the aforementioned training measurements. The results deteriorate when these conditions change e.g. through a change in the position of the patient and thus also of the ECG measuring apparatus in the magnetic resonance device, with the effect that new impulse responses that are adjusted to the changed conditions have to be estimated with the aid of further training measurements. In this way an examination of a patient would be disadvantageously extended and the stress experienced by the patient as a result of the examination would be increased.